1 citations · 1 across the 5 of their papers we have counts for
9 papers
GaussianFluent: Gaussian Simulation for Dynamic Scenes with Mixed Materials
Bei Huang, Yixin Chen, Ruijie Lu +4
3D Gaussian Splatting (3DGS) has emerged as a prominent 3D representation for high-fidelity and real-time rendering. Prior work has coupled physics simulation with Gaussians, but p…
VideoArtGS: Building Digital Twins of Articulated Objects from Monocular Video
Yu Liu, Baoxiong Jia, Ruijie Lu +5
Building digital twins of articulated objects from monocular video presents an essential challenge in computer vision, which requires simultaneous reconstruction of object geometry…
DreamArt: Generating Interactable Articulated Objects from a Single Image
Ruijie Lu, Yu Liu, Jiaxiang Tang +6
Generating articulated objects, such as laptops and microwaves, is a crucial yet challenging task with extensive applications in Embodied AI and AR/VR. Current image-to-3D methods…
Efficient Part-level 3D Object Generation via Dual Volume Packing
Jiaxiang Tang, Ruijie Lu, Zhaoshuo Li +7
Recent progress in 3D object generation has greatly improved both the quality and efficiency. However, most existing methods generate a single mesh with all parts fused together, w…
Decompositional Neural Scene Reconstruction with Generative Diffusion Prior
Junfeng Ni, Yu Liu, Ruijie Lu +4
Decompositional reconstruction of 3D scenes, with complete shapes and detailed texture of all objects within, is intriguing for downstream applications but remains challenging, par…
ArtGS: Building Interactable Replicas of Complex Articulated Objects via Gaussian Splatting
Yu Liu, Baoxiong Jia, Ruijie Lu +3
Building articulated objects is a key challenge in computer vision. Existing methods often fail to effectively integrate information across different object states, limiting the ac…